Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Nat Methods. 2018 Nov;15(11):962-968. doi: 10.1038/s41592-018-0176-y. Epub 2018 Oct 30.
Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types.
功能谱微生物群落通常是使用综合宏基因组或宏转录组序列读取搜索来生成的,这既耗时,又容易出现错误映射,并且通常仅限于社区水平的定量。我们开发了 HUMAnN2,这是一种分层搜索策略,可实现对宿主相关和环境群落进行快速、准确和物种解析的功能分析。HUMAnN2 可以识别社区的已知物种,将读取内容与泛基因组进行比对,对未分类的读取内容进行翻译搜索,最后对基因家族和途径进行定量。与纯翻译搜索相比,HUMAnN2 速度更快,生成的基因家族谱更准确。我们应用 HUMAnN2 来研究海洋代谢的渐变性、人类微生物组途径之间的生态贡献模式、物种基因组与转录组贡献的变化以及菌株分析。此外,我们引入了“贡献多样性”来解释不同微生物群落类型的生态组装模式。